Transcriptomic examination in diabetic kidney donors and pancreatic grafts
Bibliographic record
Abstract
The use of diabetic donors for kidney transplantation has increased; however, the question of the transfer of diabetic nephropathy from donor to kidney recipient remains unanswered. Therefore, gene expression profiling using microarray was used to first identify transcripts associated with diabetic nephropathy by comparing kidney donors with (n=43)/without diabetes (n=86). Four intrarenal transcripts (AKR1C2, AKR1B10, NQO1, and SERPINF2) able to discriminate donor diabetes with AUC =0.81 were identified. Their expression 3 months after transplantation from diabetic to non-diabetic recipients normalized. Those transcripts are probably induced by chronic hyperglycemia and might have a protection role against overloading with oxide radicals. Transcriptomic evaluation of rejection in kidneys and hearts using Molecular Microscope? Diagnostic System (MMDx) is available in Transplant laboratory since 2022 and is used in clinical practice. However, MMDx has not been validated for use in pancreatic grafts. The MMDx algorithm for pancreatic grafts will be created in collaboration with Alberta Transplant Applied Genomic Centre and requires large reference set of measured pancreases. IKEM as one of the most active centers in the world, with available MMDx technology, has already analyzed 77 pancreatic samples by MMDx. Only in 11 out of 77, molecular rejection was confirmed using MMDx kidney algorithm. Differential expression analysis between samples with rejection in histology (n=36) vs. no-rejection (n=35), showed upregulation of inflammatory response (p=2.8E-17), antigen-processing and presentation (p=3.7E-14) and regulation of T-cell activation (p=5.3E 14) in samples with rejection. Summary: We were able to detect early diabetic changes on a molecular level in donor kidneys without markable histologic signs of diabetic nephropathy. After transplantation of diabetic donor kidney into non-diabetic recipients, their expression normalized, supporting safety of this approach. Molecular assessment of pancreatic graft showed less rejection than histology, but sample size still needs to be larger to develop valid MMDx algorithm.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".